We use the Adam optimizer [1]} with learning rate \(\eta =0.00001\)  and batch size 128. The parameters of the encoder and generator networks are initialized with orthogonal initialization [2]}, [3]}. We set the hyperparameter \(\lambda =0.01\)  and sample \(\beta \)  from a uniform distribution, with a different random value for each training example.
